This project performs end-to-end sales analysis using SQL and Python to uncover customer behavior, revenue trends, and profitability insights from an e-commerce dataset. The goal is to understand sales performance, customer behavior, and profitability.
- What is the total revenue and profit?
- Which regions generate the most sales?
- Who are the top customers?
- How does revenue change over time?
- Do high sales always mean high profit?
- Data cleaning and preprocessing using Python (Pandas)
- Loading data into SQLite database
- Writing SQL queries to analyze sales and customer behavior
- Extracting results into Python for visualization
- Creating visualizations using Matplotlib and Seaborn
- Generating business insights from the analysis
- APAC region generates the highest sales → focus marketing there
- Sales vary over time → plan promotions in low periods
- A few customers generate most revenue → retain them
- Sales and profit do not always align → focus on profit margins
This analysis highlights that increasing sales does not always lead to higher profit, emphasizing the importance of optimizing profit margins in business strategy.
- Python (Pandas, Matplotlib, Seaborn)
- SQL (SQLite)
- vscode editor
Mouna Al-Nasser Data Analyst | BI Analyst
Open the notebook and run all cells
pip install -r requirements.txt